Searching journal content for articles similar to Antipov et al. 29 (6): 961.

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  1. Method: Strain-level metagenomic profiling using pangenome graphs with PanTax
    • Wenhai Zhang,
    • Yuansheng Liu,
    • Guangyi Li,
    • Jialu Xu,
    • Enlian Chen,
    • Alexander Schönhuth,
    • and Xiao Luo
    Genome Res. February 2026 36: 405-420; Published in Advance January 14, 2026, doi:10.1101/gr.280858.125
    .... The fundamental tasks are to classify or group sequencing reads into distinct genomic bins, each representing a different taxon (e.g., species or strain) within a metagenomic sample (taxonomic binning), and to identify the taxa present while estimating their relative abundances in the sample (taxonomic profiling...
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  2. Method: Real-time analysis and visualization of nanopore metagenomic samples with MARTi
    • Ned Peel,
    • Samuel Martin,
    • Darren Heavens,
    • Douglas W. Yu,
    • Matthew D. Clark,
    • and Richard M. Leggett
    Genome Res. November 2025 35: 2488-2500; Published in Advance October 27, 2025, doi:10.1101/gr.280550.125
    ..., it is likely to have hits to multiple species and therefore be assigned to a higher taxonomic level by the LCA algorithm. Similarly, AMR genes located on plasmids can pose a challenge as the flanking regions can often have ambiguous taxonomic hits.Generating outputThe Engine writes out analysis data and output...
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  3. Method: Accurate estimation of intraspecific microbial gene content variation in metagenomic data with MIDAS v3 and StrainPGC
    • Byron J. Smith,
    • Chunyu Zhao,
    • Veronika Dubinkina,
    • Xiaofan Jin,
    • Liron Zahavi,
    • Saar Shoer,
    • Jacqueline Moltzau-Anderson,
    • Eran Segal,
    • and Katherine S. Pollard
    Genome Res. May 2025 35: 1247-1260; Published in Advance April 10, 2025, doi:10.1101/gr.279543.124
    ...suggests clumping of the KEGG module (E) and phage or plasmid genes into co-occurrence clusters (F).Based on these de novo prevalence estimates, we assigned genes to the core (≥90% prevalence), shell (<90% and ≥15%), or cloud (<15%) pan fractions. We then calculated the portion of estimated gene content...
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  4. Method: Multiplexed long-read plasmid validation and analysis using OnRamp
    • Camille Mumm,
    • Melissa L. Drexel,
    • Torrin L. McDonald,
    • Adam G. Diehl,
    • Jessica A. Switzenberg,
    • and Alan P. Boyle
    Genome Res. May 2023 33: 741-749; Published in Advance May 8, 2023, doi:10.1101/gr.277369.122
    ...in calling homopolymers is a known limitation of ONT data (Rang et al. 2018).Next, we used this simulated data set to test OnRamp's ability to detect indels. A simulated read pool generated from a reference plasmid containing a 100-, 10-, or 1-bp insertion or deletion was added to the 30-plasmid read pool...
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  5. Method: Nanopore strand-specific mismatch enables de novo detection of bacterial DNA modifications
    • Xudong Liu,
    • Ying Ni,
    • Lianwei Ye,
    • Zhihao Guo,
    • Lu Tan,
    • Jun Li,
    • Mengsu Yang,
    • Sheng Chen,
    • and Runsheng Li
    Genome Res. November 2024 34: 2025-2038; Published in Advance October 2, 2024, doi:10.1101/gr.279012.124
    ...), and Staphylococcus aureus (Wang et al. 2017). We identified patterns of unbalanced mismatches between forward and reverse strands on these s. The sequences of these Gram-negative and Gram-positive strains differ in terms of complexity in chromosomes and plasmids, and these strains can be used as representatives...
  6. Method: Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates
    • Tyler A. Joseph,
    • Philippe Chlenski,
    • Aviya Litman,
    • Tal Korem,
    • and Itsik Pe'er
    Genome Res. March 2022 32: 558-568; Published in Advance January 5, 2022, doi:10.1101/gr.275533.121
    ...). Nonetheless, PTR estimates by KoremPTR were highly correlated with the ground truth (Pearson r > 0.88). We saw the same pattern across six genomic (bacteria grown in monoculture) and metagenomic data sets (Fig. 2C). Both methods were correlated, but CoPTR-Ref estimated larger PTRs than did Korem...
  7. Method: Precise genotyping of circular mobile elements from metagenomic data uncovers human-associated plasmids with recent common ancestors
    • Nitan Shalon,
    • David A. Relman,
    • and Eitan Yaffe
    Genome Res. May 2022 32: 986-1003; Published in Advance April 12, 2022, doi:10.1101/gr.275894.121
    ...and real sequencing data. Application of DomCycle to 32 publicly available DNA shotgun sequence data sets from diverse natural environments led to the reconstruction of hundreds of circular mobile s. Clustering revealed 20 highly prevalent and cryptic plasmids that have clonal population structures...
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  8. Review: Data structures based on k-mers for querying large collections of sequencing data sets
    • Camille Marchet,
    • Christina Boucher,
    • Simon J. Puglisi,
    • Paul Medvedev,
    • Mikaël Salson,
    • and Rayan Chikhi
    Genome Res. January 2021 31: 1-12; Published in Advance December 16, 2020, doi:10.1101/gr.260604.119
    ...elucidate the effectiveness of interventions that attempt to control them.Subsequently, k-mer indices have been used to follow the spread of antimicrobial resistance (AMR) genes and plasmids across bacterial populations. The BIGSI authors also searched for plasmid sequences bearing AMR and initiated a study...
  9. Method: High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic Nanopore sequencing
    • Nicholas D. Sanderson,
    • Jeremy Swann,
    • Leanne Barker,
    • James Kavanagh,
    • Sarah Hoosdally,
    • Derrick Crook,
    • The GonFast Investigators Group,
    • Teresa L. Street,
    • and David W. Eyre
    Genome Res. September 2020 30: 1354-1363; Published in Advance September 1, 2020, doi:10.1101/gr.262865.120
    ...at lower read coverage, but did not provide as much genomic context.Detection of plasmid-mediated resistance determinantsPlasmid-carried tetM and blaTEM-1 confer tetracycline and penicillin resistance, respectively. Reads containing tetM or blaTEM-1 sequence were extracted and assembled. To determine...
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  10. Method: Subgenomic RNA identification in SARS-CoV-2 genomic sequencing data
    • Matthew D. Parker,
    • Benjamin B. Lindsey,
    • Shay Leary,
    • Silvana Gaudieri,
    • Abha Chopra,
    • Matthew Wyles,
    • Adrienn Angyal,
    • Luke R. Green,
    • Paul Parsons,
    • Rachel M. Tucker,
    • Rebecca Brown,
    • Danielle Groves,
    • Katie Johnson,
    • Laura Carrilero,
    • Joe Heffer,
    • David G. Partridge,
    • Cariad Evans,
    • Mohammad Raza,
    • Alexander J. Keeley,
    • Nikki Smith,
    • Ana Da Silva Filipe,
    • James G. Shepherd,
    • Chris Davis,
    • Sahan Bennett,
    • Vattipally B. Sreenu,
    • Alain Kohl,
    • Elihu Aranday-Cortes,
    • Lily Tong,
    • Jenna Nichols,
    • Emma C. Thomson,
    • The COVID-19 Genomics UK (COG-UK) Consortium,
    • Dennis Wang,
    • Simon Mallal,
    • and Thushan I. de Silva
    Genome Res. April 2021 31: 645-658; Published in Advance March 15, 2021, doi:10.1101/gr.268110.120
    ...number of reads for sgRNA analysis. In VeroE6 ACE2+/− cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing data sets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced...
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